The oxide etch rate of a single chamber of plasma etch tool is estimated from plasma impedance data collected during the etch process. The etch rate is estimated using a linear statistical model and etch rate measurements performed on special test wafers. Stepwise regression is used to select possible predictors from a large pool of summary statistics calculated from the plasma impedance waveforms. The relationship of the estimated mean etch rate to yield and potential yield optimization is explored. An example application of an
advanced process controller to optimize the yield of the wafers processed by the etch tool in the presence of varying chamber conditions is also presented.